A Multi‐queue Approach of Energy Efficient Task Scheduling for Sensor Hubs

Huang, Jiwei; Zhang, Chenxiang; Zhang, Jianbing

doi:10.1049/cje.2020.02.001

Cited by 58 publications

(35 citation statements)

References 17 publications

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“…In [34], we introduced simulation techniques to queueing models and designed an optimization scheme of service selection for mobile edge computing. In [35], based on the queueing model, we formulated a stochastic optimization problem of energy efficient task scheduling for sensor hubs in IoT, and designed an efficient scheme to solve the problem. In [36], we further studied the task scheduling and resource management problem in mobile edge computing by designing a more efficient optimization algorithm.…”

Section: Discussionmentioning

confidence: 99%

A Simulation-Based Optimization Approach for Reliability-Aware Service Composition in Edge Computing

2020

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With the prevalence of Internet of Things (IoT), edge computing has emerged as a novel computing model for optimizing traditional cloud computing systems by moving part of the computational tasks to the edge of the network for better performance and security. With the technique of services computing, edge computing systems can accommodate the application requirements with more agility and flexibility. In large-scale edge computing systems, service composition as one of the most important problems in services computing suffers from several new challenges, i.e., complex layered architecture, failures and recoveries always in the lifecycle, and search space explosion. In this paper, we make an attempt at addressing these challenges by designing a simulation-based optimization approach for reliability-aware service composition. Composite stochastic Petri net models are proposed for formulating the dynamics of multi-layered edge computing systems, and their corresponding quantitative analysis is conducted. To solve the state explosion problem in large-scale systems or complex service processes, time scale decomposition technique is applied to improving the efficiency of model solving. Additionally, simulation schemes are designed for performance evaluation and optimization, and ordinal optimization technique is introduced to significantly reduce the size of the search space. Finally, we conduct experiments based on real-life data, and the empirical results validate the efficacy of the approach.

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Section: Discussionmentioning

confidence: 99%

A Simulation-Based Optimization Approach for Reliability-Aware Service Composition in Edge Computing

2020

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“…We have applied queueing network model to the performance evaluation of IoT services deployed in edge computing paradigm [31], and further put forward a simulation-based optimization approach of efficient service selection [32]. With queueing theory, we also proposed a multiqueue approach of energyefficient task scheduling for sensor hubs in IoT using Lyapunov optimization technique [33]. In [34], we investigated the task scheduling and resource management problem and designed an equivalent linear programming problem which could be efficiently and elegantly solved at polynomial computational complexity.…”

Section: Discussionmentioning

confidence: 99%

Deploying GIS Services into the Edge: A Study from Performance Evaluation and Optimization Viewpoint

Zhang

Huang

2020

Security and Communication Networks

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Geographic information system (GIS) is an integrated collection of computer software and data used to view and manage information about geographic places, analyze spatial relationships, and model spatial processes. With the growing popularity and wide application of GIS in reality, performance has become a critical requirement, especially for mobile GIS services. To attack this challenge, this paper tries to optimize the performance of GIS services by deploying them into edge computing architecture which is an emerging computational model that enables efficient offloading of service requests to edge servers for reducing the communication latency between end-users and GIS servers deployed in the cloud. Stochastic models for describing the dynamics of GIS services with edge computing architecture are presented, and their corresponding quantitative analyses of performance attributes are provided. Furthermore, an optimization problem is formulated for service deployment in such architecture, and a heuristic approach to obtain the near-optimal performance is designed. Simulation experiments based on real-life GIS performance data are conducted to validate the effectiveness of the approach presented in this paper.

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“…With the rapid development of vehicle wireless communication technology, Internet of vehicles (IoV) has a broad development prospect [1]. Among the various applications generated by IoV, security applications are undoubtedly of the highest priority because they impact on the safety of the vehicles directly [2]. Vehicle-to-Vehicle (V2V) communication as a key technology in intelligent transportation system (ITS) that could meet the strict latency and reliability requirements of safety applications has attracted continuous academic attention [3].…”

Section: Introductionmentioning

confidence: 99%

Energy‐Efficient Resource Allocation for NOMA‐Enabled Internet of Vehicles

Chen

et al. 2021

Wireless Communications and Mobile Computing

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With the rapid development of Internet of vehicles (IoV) technology, the distribution of vehicles on the highway becomes more dense and the highly reliable communication between vehicles becomes more important. Nonorthogonal multiple access (NOMA) is a promising technology to meet the multiple access volume and the high reliability communication demands of IoV. To meet the Vehicle-to-Vehicle (V2V) communication requirements, a NOMA-based IoV system is proposed. Firstly, a NOMA-based resource allocation model in IoV is developed to maximize the energy efficiency (EE) of the system. Secondly, the established model is transformed into a Markov decision process (MDP) model and a deep reinforcement learning-based subchannel and power allocation (DSPA) algorithm is designed. An event trigger block is used to reduce computation time. Finally, the simulation results show that NOMA can significantly improve the system performance compared to orthogonal multiaccess, and the proposed DSPA algorithm can significantly improve the system EE and reduce the computation time.

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A Multi‐queue Approach of Energy Efficient Task Scheduling for Sensor Hubs

Cited by 58 publications

References 17 publications

A Simulation-Based Optimization Approach for Reliability-Aware Service Composition in Edge Computing

A Simulation-Based Optimization Approach for Reliability-Aware Service Composition in Edge Computing

Deploying GIS Services into the Edge: A Study from Performance Evaluation and Optimization Viewpoint

Energy‐Efficient Resource Allocation for NOMA‐Enabled Internet of Vehicles

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